This article talks about multi-agent collaboration very well. I have recently observed...

This article talks about multi-agent collaboration very well.

I have recently observed that starting from Calude’s multi-agent architecture article on building deep research, to Claude Code @claudeai’s sub-agent collaboration, and then to the recent wide research launched by manus @manusai, hundreds of sub-agents can be implemented at the same time.

Judging from the trend, the current trend of multi-agent architecture is that one master agent is responsible for controlling the scheduling, arranging each sub agent to perform tasks, and at the same time summarizing the results of the sub agents, and then calling one after merging.

Some tools output content as required.

The advantage of this is that it can ensure that important information during the complete life cycle of a long and complex task is not lost, and the corresponding sub agent only gets the context it needs, avoiding the problem of context information explosion when multiple agents collaborate.

My understanding of a sub agent is that it has the minimum capabilities of an AI agent but only completes a certain type of specific tasks.

The advantage of this is to reduce the total token required for the overall agent architecture and reduce information synchronization.

Short and fast processing brings the possibility of high concurrency for multiple agents.

The performance is obviously improved, and the long tasks we will experience in the future will become faster and faster.

Of course, a lot of optimization is required at the engineering level, otherwise it will easily cause problems such as a huge number of tokens, context overflow, and task failure.

This should be a very familiar flavor to software architects.

Similar to the microservice architecture of traditional software and the controller-node architecture of k8s, there are many problems that will only appear after the measurement is carried out.

The architecture design and optimization will be carried out in advance, and engineering ingenuity and design patterns will be implemented one after another.

So this is a good start for AI Agent!

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